Overview

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Dataset statistics

Number of variables16
Number of observations1000
Missing cells427
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory1.0 KiB

Variable types

URL1
Text11
Categorical1
Numeric3

Alerts

Certificate has 101 (10.1%) missing values Missing
Meta_score has 157 (15.7%) missing values Missing
Gross has 169 (16.9%) missing values Missing
Poster_Link has unique values Unique
Overview has unique values Unique

Reproduction

Analysis started2025-03-11 00:30:22.918167
Analysis finished2025-03-11 00:30:24.442941
Duration1.52 second
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

Poster_Link
URL

Unique 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size181.4 KiB
https://m.media-amazon.com/images/M/MV5BMTY5ODAzMTcwOF5BMl5BanBnXkFtZTcwMzYxNDYyNA@@._V1_UX67_CR0,0,67,98_AL_.jpg
 
1
https://m.media-amazon.com/images/M/MV5BMDFkYTc0MGEtZmNhMC00ZDIzLWFmNTEtODM1ZmRlYWMwMWFmXkEyXkFqcGdeQXVyMTMxODk2OTU@._V1_UX67_CR0,0,67,98_AL_.jpg
 
1
https://m.media-amazon.com/images/M/MV5BM2MyNjYxNmUtYTAwNi00MTYxLWJmNWYtYzZlODY3ZTk3OTFlXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpg
 
1
https://m.media-amazon.com/images/M/MV5BMTMxNTMwODM0NF5BMl5BanBnXkFtZTcwODAyMTk2Mw@@._V1_UX67_CR0,0,67,98_AL_.jpg
 
1
https://m.media-amazon.com/images/M/MV5BMWMwMGQzZTItY2JlNC00OWZiLWIyMDctNDk2ZDQ2YjRjMWQ0XkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpg
 
1
Other values (995)
995 
ValueCountFrequency (%)
https://m.media-amazon.com/images/M/MV5BMTY5ODAzMTcwOF5BMl5BanBnXkFtZTcwMzYxNDYyNA@@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BMDFkYTc0MGEtZmNhMC00ZDIzLWFmNTEtODM1ZmRlYWMwMWFmXkEyXkFqcGdeQXVyMTMxODk2OTU@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BM2MyNjYxNmUtYTAwNi00MTYxLWJmNWYtYzZlODY3ZTk3OTFlXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BMTMxNTMwODM0NF5BMl5BanBnXkFtZTcwODAyMTk2Mw@@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BMWMwMGQzZTItY2JlNC00OWZiLWIyMDctNDk2ZDQ2YjRjMWQ0XkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BMWU4N2FjNzYtNTVkNC00NzQ0LTg0MjAtYTJlMjFhNGUxZDFmXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BNzA5ZDNlZWMtM2NhNS00NDJjLTk4NDItYTRmY2EwMWZlMTY3XkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BNGNhMDIzZTUtNTBlZi00MTRlLWFjM2ItYzViMjE3YzI5MjljXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR0,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BYTU2MWRiMTMtYzAzZi00NGYzLTlkMDEtNWQ3MzZlNTJlNzZkL2ltYWdlL2ltYWdlXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
https://m.media-amazon.com/images/M/MV5BN2VlNjNhZWQtMTY2OC00Y2E1LWJkNGUtMDU4M2ViNzliMGYwXkEyXkFqcGdeQXVyNTAyODkwOQ@@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
https 1000
100.0%
ValueCountFrequency (%)
m.media-amazon.com 1000
100.0%
ValueCountFrequency (%)
/images/M/MV5BMTY5ODAzMTcwOF5BMl5BanBnXkFtZTcwMzYxNDYyNA@@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BMDFkYTc0MGEtZmNhMC00ZDIzLWFmNTEtODM1ZmRlYWMwMWFmXkEyXkFqcGdeQXVyMTMxODk2OTU@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BM2MyNjYxNmUtYTAwNi00MTYxLWJmNWYtYzZlODY3ZTk3OTFlXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BMTMxNTMwODM0NF5BMl5BanBnXkFtZTcwODAyMTk2Mw@@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BMWMwMGQzZTItY2JlNC00OWZiLWIyMDctNDk2ZDQ2YjRjMWQ0XkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BMWU4N2FjNzYtNTVkNC00NzQ0LTg0MjAtYTJlMjFhNGUxZDFmXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BNzA5ZDNlZWMtM2NhNS00NDJjLTk4NDItYTRmY2EwMWZlMTY3XkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BNGNhMDIzZTUtNTBlZi00MTRlLWFjM2ItYzViMjE3YzI5MjljXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR0,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BYTU2MWRiMTMtYzAzZi00NGYzLTlkMDEtNWQ3MzZlNTJlNzZkL2ltYWdlL2ltYWdlXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
/images/M/MV5BN2VlNjNhZWQtMTY2OC00Y2E1LWJkNGUtMDU4M2ViNzliMGYwXkEyXkFqcGdeQXVyNTAyODkwOQ@@._V1_UX67_CR0,0,67,98_AL_.jpg 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1000
100.0%
ValueCountFrequency (%)
1000
100.0%
Distinct999
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size64.9 KiB
2025-03-10T21:30:24.675203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length68
Median length41
Mean length15.452
Min length2

Characters and Unicode

Total characters15452
Distinct characters100
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique998 ?
Unique (%)99.8%

Sample

1st rowThe Shawshank Redemption
2nd rowThe Godfather
3rd rowThe Dark Knight
4th rowThe Godfather: Part II
5th row12 Angry Men
ValueCountFrequency (%)
the 275
 
9.9%
of 86
 
3.1%
a 32
 
1.1%
and 28
 
1.0%
no 24
 
0.9%
la 23
 
0.8%
in 22
 
0.8%
to 18
 
0.6%
man 17
 
0.6%
de 17
 
0.6%
Other values (1666) 2243
80.5%
2025-03-10T21:30:25.033833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1785
 
11.6%
e 1428
 
9.2%
a 1128
 
7.3%
o 966
 
6.3%
n 923
 
6.0%
i 862
 
5.6%
r 816
 
5.3%
t 756
 
4.9%
h 567
 
3.7%
s 563
 
3.6%
Other values (90) 5658
36.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15452
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1785
 
11.6%
e 1428
 
9.2%
a 1128
 
7.3%
o 966
 
6.3%
n 923
 
6.0%
i 862
 
5.6%
r 816
 
5.3%
t 756
 
4.9%
h 567
 
3.7%
s 563
 
3.6%
Other values (90) 5658
36.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15452
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1785
 
11.6%
e 1428
 
9.2%
a 1128
 
7.3%
o 966
 
6.3%
n 923
 
6.0%
i 862
 
5.6%
r 816
 
5.3%
t 756
 
4.9%
h 567
 
3.7%
s 563
 
3.6%
Other values (90) 5658
36.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15452
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1785
 
11.6%
e 1428
 
9.2%
a 1128
 
7.3%
o 966
 
6.3%
n 923
 
6.0%
i 862
 
5.6%
r 816
 
5.3%
t 756
 
4.9%
h 567
 
3.7%
s 563
 
3.6%
Other values (90) 5658
36.6%
Distinct100
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
2025-03-10T21:30:25.217536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.998
Min length2

Characters and Unicode

Total characters3998
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.0%

Sample

1st row1994
2nd row1972
3rd row2008
4th row1974
5th row1957
ValueCountFrequency (%)
2014 32
 
3.2%
2004 31
 
3.1%
2009 29
 
2.9%
2013 28
 
2.8%
2016 28
 
2.8%
2001 27
 
2.7%
2006 26
 
2.6%
2007 26
 
2.6%
2015 25
 
2.5%
2012 24
 
2.4%
Other values (90) 724
72.4%
2025-03-10T21:30:25.521349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 842
21.1%
0 814
20.4%
9 774
19.4%
2 599
15.0%
8 187
 
4.7%
7 182
 
4.6%
6 172
 
4.3%
5 152
 
3.8%
4 146
 
3.7%
3 128
 
3.2%
Other values (2) 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3998
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 842
21.1%
0 814
20.4%
9 774
19.4%
2 599
15.0%
8 187
 
4.7%
7 182
 
4.6%
6 172
 
4.3%
5 152
 
3.8%
4 146
 
3.7%
3 128
 
3.2%
Other values (2) 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3998
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 842
21.1%
0 814
20.4%
9 774
19.4%
2 599
15.0%
8 187
 
4.7%
7 182
 
4.6%
6 172
 
4.3%
5 152
 
3.8%
4 146
 
3.7%
3 128
 
3.2%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3998
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 842
21.1%
0 814
20.4%
9 774
19.4%
2 599
15.0%
8 187
 
4.7%
7 182
 
4.6%
6 172
 
4.3%
5 152
 
3.8%
4 146
 
3.7%
3 128
 
3.2%
Other values (2) 2
 
0.1%

Certificate
Categorical

Missing 

Distinct16
Distinct (%)1.8%
Missing101
Missing (%)10.1%
Memory size50.2 KiB
U
234 
A
197 
UA
175 
R
146 
PG-13
43 
Other values (11)
104 

Length

Max length8
Median length1
Mean length1.7363737
Min length1

Characters and Unicode

Total characters1561
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.6%

Sample

1st rowA
2nd rowA
3rd rowUA
4th rowA
5th rowU

Common Values

ValueCountFrequency (%)
U 234
23.4%
A 197
19.7%
UA 175
17.5%
R 146
14.6%
PG-13 43
 
4.3%
PG 37
 
3.7%
Passed 34
 
3.4%
G 12
 
1.2%
Approved 11
 
1.1%
TV-PG 3
 
0.3%
Other values (6) 7
 
0.7%
(Missing) 101
10.1%

Length

2025-03-10T21:30:25.611367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
u 234
26.0%
a 197
21.9%
ua 175
19.5%
r 146
16.2%
pg-13 43
 
4.8%
pg 37
 
4.1%
passed 34
 
3.8%
g 12
 
1.3%
approved 11
 
1.2%
tv-pg 3
 
0.3%
Other values (6) 7
 
0.8%

Most occurring characters

ValueCountFrequency (%)
U 411
26.3%
A 385
24.7%
R 146
 
9.4%
P 119
 
7.6%
G 97
 
6.2%
s 68
 
4.4%
- 48
 
3.1%
e 46
 
2.9%
d 46
 
2.9%
1 45
 
2.9%
Other values (14) 150
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1561
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 411
26.3%
A 385
24.7%
R 146
 
9.4%
P 119
 
7.6%
G 97
 
6.2%
s 68
 
4.4%
- 48
 
3.1%
e 46
 
2.9%
d 46
 
2.9%
1 45
 
2.9%
Other values (14) 150
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1561
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 411
26.3%
A 385
24.7%
R 146
 
9.4%
P 119
 
7.6%
G 97
 
6.2%
s 68
 
4.4%
- 48
 
3.1%
e 46
 
2.9%
d 46
 
2.9%
1 45
 
2.9%
Other values (14) 150
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1561
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 411
26.3%
A 385
24.7%
R 146
 
9.4%
P 119
 
7.6%
G 97
 
6.2%
s 68
 
4.4%
- 48
 
3.1%
e 46
 
2.9%
d 46
 
2.9%
1 45
 
2.9%
Other values (14) 150
 
9.6%
Distinct140
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size54.6 KiB
2025-03-10T21:30:25.800667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.815
Min length6

Characters and Unicode

Total characters6815
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)3.5%

Sample

1st row142 min
2nd row175 min
3rd row152 min
4th row202 min
5th row96 min
ValueCountFrequency (%)
min 1000
50.0%
100 23
 
1.1%
130 23
 
1.1%
129 22
 
1.1%
101 22
 
1.1%
113 22
 
1.1%
110 20
 
1.0%
122 20
 
1.0%
108 19
 
0.9%
102 18
 
0.9%
Other values (131) 811
40.6%
2025-03-10T21:30:26.052312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1047
15.4%
1000
14.7%
i 1000
14.7%
m 1000
14.7%
n 1000
14.7%
0 305
 
4.5%
2 278
 
4.1%
9 224
 
3.3%
3 219
 
3.2%
8 172
 
2.5%
Other values (4) 570
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6815
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1047
15.4%
1000
14.7%
i 1000
14.7%
m 1000
14.7%
n 1000
14.7%
0 305
 
4.5%
2 278
 
4.1%
9 224
 
3.3%
3 219
 
3.2%
8 172
 
2.5%
Other values (4) 570
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6815
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1047
15.4%
1000
14.7%
i 1000
14.7%
m 1000
14.7%
n 1000
14.7%
0 305
 
4.5%
2 278
 
4.1%
9 224
 
3.3%
3 219
 
3.2%
8 172
 
2.5%
Other values (4) 570
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6815
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1047
15.4%
1000
14.7%
i 1000
14.7%
m 1000
14.7%
n 1000
14.7%
0 305
 
4.5%
2 278
 
4.1%
9 224
 
3.3%
3 219
 
3.2%
8 172
 
2.5%
Other values (4) 570
8.4%

Genre
Text

Distinct202
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size66.6 KiB
2025-03-10T21:30:26.148962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length29
Median length24
Mean length19.063
Min length5

Characters and Unicode

Total characters19063
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)7.2%

Sample

1st rowDrama
2nd rowCrime, Drama
3rd rowAction, Crime, Drama
4th rowCrime, Drama
5th rowCrime, Drama
ValueCountFrequency (%)
drama 724
28.5%
comedy 233
 
9.2%
crime 209
 
8.2%
adventure 196
 
7.7%
action 189
 
7.4%
thriller 137
 
5.4%
romance 125
 
4.9%
biography 109
 
4.3%
mystery 99
 
3.9%
animation 82
 
3.2%
Other values (11) 438
17.2%
2025-03-10T21:30:26.328669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2020
 
10.6%
r 1872
 
9.8%
, 1541
 
8.1%
1541
 
8.1%
m 1448
 
7.6%
e 1235
 
6.5%
i 1144
 
6.0%
o 896
 
4.7%
n 760
 
4.0%
t 727
 
3.8%
Other values (23) 5879
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19063
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2020
 
10.6%
r 1872
 
9.8%
, 1541
 
8.1%
1541
 
8.1%
m 1448
 
7.6%
e 1235
 
6.5%
i 1144
 
6.0%
o 896
 
4.7%
n 760
 
4.0%
t 727
 
3.8%
Other values (23) 5879
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19063
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2020
 
10.6%
r 1872
 
9.8%
, 1541
 
8.1%
1541
 
8.1%
m 1448
 
7.6%
e 1235
 
6.5%
i 1144
 
6.0%
o 896
 
4.7%
n 760
 
4.0%
t 727
 
3.8%
Other values (23) 5879
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19063
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2020
 
10.6%
r 1872
 
9.8%
, 1541
 
8.1%
1541
 
8.1%
m 1448
 
7.6%
e 1235
 
6.5%
i 1144
 
6.0%
o 896
 
4.7%
n 760
 
4.0%
t 727
 
3.8%
Other values (23) 5879
30.8%

IMDB_Rating
Real number (ℝ)

Distinct17
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9493
Minimum7.6
Maximum9.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-03-10T21:30:26.388265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum7.6
5-th percentile7.6
Q17.7
median7.9
Q38.1
95-th percentile8.5
Maximum9.3
Range1.7
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.27549121
Coefficient of variation (CV)0.034656034
Kurtosis1.432727
Mean7.9493
Median Absolute Deviation (MAD)0.2
Skewness1.0169645
Sum7949.3
Variance0.075895405
MonotonicityDecreasing
2025-03-10T21:30:26.454919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
7.7 157
15.7%
7.8 151
15.1%
8 141
14.1%
8.1 127
12.7%
7.6 123
12.3%
7.9 106
10.6%
8.2 67
6.7%
8.3 44
 
4.4%
8.4 31
 
3.1%
8.5 20
 
2.0%
Other values (7) 33
 
3.3%
ValueCountFrequency (%)
7.6 123
12.3%
7.7 157
15.7%
7.8 151
15.1%
7.9 106
10.6%
8 141
14.1%
8.1 127
12.7%
8.2 67
6.7%
8.3 44
 
4.4%
8.4 31
 
3.1%
8.5 20
 
2.0%
ValueCountFrequency (%)
9.3 1
 
0.1%
9.2 1
 
0.1%
9 3
 
0.3%
8.9 3
 
0.3%
8.8 5
 
0.5%
8.7 5
 
0.5%
8.6 15
 
1.5%
8.5 20
2.0%
8.4 31
3.1%
8.3 44
4.4%

Overview
Text

Unique 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size193.6 KiB
2025-03-10T21:30:26.692178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length313
Median length196.5
Mean length146.255
Min length40

Characters and Unicode

Total characters146255
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowTwo imprisoned men bond over a number of years, finding solace and eventual redemption through acts of common decency.
2nd rowAn organized crime dynasty's aging patriarch transfers control of his clandestine empire to his reluctant son.
3rd rowWhen the menace known as the Joker wreaks havoc and chaos on the people of Gotham, Batman must accept one of the greatest psychological and physical tests of his ability to fight injustice.
4th rowThe early life and career of Vito Corleone in 1920s New York City is portrayed, while his son, Michael, expands and tightens his grip on the family crime syndicate.
5th rowA jury holdout attempts to prevent a miscarriage of justice by forcing his colleagues to reconsider the evidence.
ValueCountFrequency (%)
a 1610
 
6.4%
the 1206
 
4.8%
to 803
 
3.2%
of 779
 
3.1%
and 697
 
2.8%
in 565
 
2.3%
his 516
 
2.1%
an 291
 
1.2%
is 245
 
1.0%
with 242
 
1.0%
Other values (5880) 18049
72.2%
2025-03-10T21:30:27.035781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24017
16.4%
e 13879
 
9.5%
a 9806
 
6.7%
t 9333
 
6.4%
i 8847
 
6.0%
n 8591
 
5.9%
o 8570
 
5.9%
r 8208
 
5.6%
s 7969
 
5.4%
h 5627
 
3.8%
Other values (76) 41408
28.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 146255
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
24017
16.4%
e 13879
 
9.5%
a 9806
 
6.7%
t 9333
 
6.4%
i 8847
 
6.0%
n 8591
 
5.9%
o 8570
 
5.9%
r 8208
 
5.6%
s 7969
 
5.4%
h 5627
 
3.8%
Other values (76) 41408
28.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 146255
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
24017
16.4%
e 13879
 
9.5%
a 9806
 
6.7%
t 9333
 
6.4%
i 8847
 
6.0%
n 8591
 
5.9%
o 8570
 
5.9%
r 8208
 
5.6%
s 7969
 
5.4%
h 5627
 
3.8%
Other values (76) 41408
28.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 146255
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
24017
16.4%
e 13879
 
9.5%
a 9806
 
6.7%
t 9333
 
6.4%
i 8847
 
6.0%
n 8591
 
5.9%
o 8570
 
5.9%
r 8208
 
5.6%
s 7969
 
5.4%
h 5627
 
3.8%
Other values (76) 41408
28.3%

Meta_score
Real number (ℝ)

Missing 

Distinct63
Distinct (%)7.5%
Missing157
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean77.97153
Minimum28
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-03-10T21:30:27.117842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile56
Q170
median79
Q387
95-th percentile96
Maximum100
Range72
Interquartile range (IQR)17

Descriptive statistics

Standard deviation12.376099
Coefficient of variation (CV)0.15872587
Kurtosis0.42083062
Mean77.97153
Median Absolute Deviation (MAD)8
Skewness-0.60522483
Sum65730
Variance153.16783
MonotonicityNot monotonic
2025-03-10T21:30:27.212441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76 32
 
3.2%
84 29
 
2.9%
90 29
 
2.9%
73 27
 
2.7%
85 27
 
2.7%
86 27
 
2.7%
80 27
 
2.7%
72 27
 
2.7%
81 26
 
2.6%
77 26
 
2.6%
Other values (53) 566
56.6%
(Missing) 157
 
15.7%
ValueCountFrequency (%)
28 1
 
0.1%
30 1
 
0.1%
33 1
 
0.1%
36 1
 
0.1%
40 1
 
0.1%
41 1
 
0.1%
44 1
 
0.1%
45 3
0.3%
46 1
 
0.1%
47 4
0.4%
ValueCountFrequency (%)
100 12
1.2%
99 4
 
0.4%
98 9
0.9%
97 12
1.2%
96 18
1.8%
95 11
1.1%
94 20
2.0%
93 14
1.4%
92 13
1.3%
91 19
1.9%
Distinct548
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size62.6 KiB
2025-03-10T21:30:27.450390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length32
Median length22
Mean length13.486
Min length7

Characters and Unicode

Total characters13486
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique352 ?
Unique (%)35.2%

Sample

1st rowFrank Darabont
2nd rowFrancis Ford Coppola
3rd rowChristopher Nolan
4th rowFrancis Ford Coppola
5th rowSidney Lumet
ValueCountFrequency (%)
john 34
 
1.6%
david 28
 
1.4%
james 23
 
1.1%
robert 20
 
1.0%
martin 16
 
0.8%
richard 15
 
0.7%
lee 15
 
0.7%
stanley 14
 
0.7%
george 14
 
0.7%
alfred 14
 
0.7%
Other values (882) 1881
90.7%
2025-03-10T21:30:27.785630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1209
 
9.0%
a 1129
 
8.4%
1074
 
8.0%
n 952
 
7.1%
r 919
 
6.8%
o 852
 
6.3%
i 834
 
6.2%
l 543
 
4.0%
s 497
 
3.7%
t 434
 
3.2%
Other values (59) 5043
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13486
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1209
 
9.0%
a 1129
 
8.4%
1074
 
8.0%
n 952
 
7.1%
r 919
 
6.8%
o 852
 
6.3%
i 834
 
6.2%
l 543
 
4.0%
s 497
 
3.7%
t 434
 
3.2%
Other values (59) 5043
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13486
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1209
 
9.0%
a 1129
 
8.4%
1074
 
8.0%
n 952
 
7.1%
r 919
 
6.8%
o 852
 
6.3%
i 834
 
6.2%
l 543
 
4.0%
s 497
 
3.7%
t 434
 
3.2%
Other values (59) 5043
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13486
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1209
 
9.0%
a 1129
 
8.4%
1074
 
8.0%
n 952
 
7.1%
r 919
 
6.8%
o 852
 
6.3%
i 834
 
6.2%
l 543
 
4.0%
s 497
 
3.7%
t 434
 
3.2%
Other values (59) 5043
37.4%

Star1
Text

Distinct660
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size62.2 KiB
2025-03-10T21:30:28.044384image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length25
Median length21
Mean length13.003
Min length4

Characters and Unicode

Total characters13003
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique503 ?
Unique (%)50.3%

Sample

1st rowTim Robbins
2nd rowMarlon Brando
3rd rowChristian Bale
4th rowAl Pacino
5th rowHenry Fonda
ValueCountFrequency (%)
tom 22
 
1.1%
daniel 17
 
0.8%
robert 17
 
0.8%
john 16
 
0.8%
khan 16
 
0.8%
james 15
 
0.7%
hanks 12
 
0.6%
michael 12
 
0.6%
de 11
 
0.5%
al 11
 
0.5%
Other values (1113) 1900
92.7%
2025-03-10T21:30:28.508304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1239
 
9.5%
e 1088
 
8.4%
1049
 
8.1%
n 952
 
7.3%
r 816
 
6.3%
i 796
 
6.1%
o 768
 
5.9%
l 590
 
4.5%
t 453
 
3.5%
s 439
 
3.4%
Other values (62) 4813
37.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13003
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1239
 
9.5%
e 1088
 
8.4%
1049
 
8.1%
n 952
 
7.3%
r 816
 
6.3%
i 796
 
6.1%
o 768
 
5.9%
l 590
 
4.5%
t 453
 
3.5%
s 439
 
3.4%
Other values (62) 4813
37.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13003
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1239
 
9.5%
e 1088
 
8.4%
1049
 
8.1%
n 952
 
7.3%
r 816
 
6.3%
i 796
 
6.1%
o 768
 
5.9%
l 590
 
4.5%
t 453
 
3.5%
s 439
 
3.4%
Other values (62) 4813
37.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13003
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1239
 
9.5%
e 1088
 
8.4%
1049
 
8.1%
n 952
 
7.3%
r 816
 
6.3%
i 796
 
6.1%
o 768
 
5.9%
l 590
 
4.5%
t 453
 
3.5%
s 439
 
3.4%
Other values (62) 4813
37.0%

Star2
Text

Distinct841
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size62.5 KiB
2025-03-10T21:30:28.732399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length25
Median length22
Mean length13.123
Min length4

Characters and Unicode

Total characters13123
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique729 ?
Unique (%)72.9%

Sample

1st rowMorgan Freeman
2nd rowAl Pacino
3rd rowHeath Ledger
4th rowRobert De Niro
5th rowLee J. Cobb
ValueCountFrequency (%)
john 21
 
1.0%
robert 16
 
0.8%
lee 13
 
0.6%
michael 13
 
0.6%
emma 10
 
0.5%
chris 9
 
0.4%
james 9
 
0.4%
jack 8
 
0.4%
tom 8
 
0.4%
george 8
 
0.4%
Other values (1389) 1942
94.4%
2025-03-10T21:30:29.019803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1321
 
10.1%
e 1182
 
9.0%
1057
 
8.1%
n 951
 
7.2%
r 887
 
6.8%
i 785
 
6.0%
o 720
 
5.5%
l 579
 
4.4%
t 483
 
3.7%
s 432
 
3.3%
Other values (59) 4726
36.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13123
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1321
 
10.1%
e 1182
 
9.0%
1057
 
8.1%
n 951
 
7.2%
r 887
 
6.8%
i 785
 
6.0%
o 720
 
5.5%
l 579
 
4.4%
t 483
 
3.7%
s 432
 
3.3%
Other values (59) 4726
36.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13123
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1321
 
10.1%
e 1182
 
9.0%
1057
 
8.1%
n 951
 
7.2%
r 887
 
6.8%
i 785
 
6.0%
o 720
 
5.5%
l 579
 
4.4%
t 483
 
3.7%
s 432
 
3.3%
Other values (59) 4726
36.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13123
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1321
 
10.1%
e 1182
 
9.0%
1057
 
8.1%
n 951
 
7.2%
r 887
 
6.8%
i 785
 
6.0%
o 720
 
5.5%
l 579
 
4.4%
t 483
 
3.7%
s 432
 
3.3%
Other values (59) 4726
36.0%

Star3
Text

Distinct891
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size62.3 KiB
2025-03-10T21:30:29.228110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length27
Median length21
Mean length13.28
Min length4

Characters and Unicode

Total characters13280
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique809 ?
Unique (%)80.9%

Sample

1st rowBob Gunton
2nd rowJames Caan
3rd rowAaron Eckhart
4th rowRobert Duvall
5th rowMartin Balsam
ValueCountFrequency (%)
john 21
 
1.0%
robert 16
 
0.8%
michael 13
 
0.6%
richard 12
 
0.6%
christopher 9
 
0.4%
paul 8
 
0.4%
jack 8
 
0.4%
harris 7
 
0.3%
george 7
 
0.3%
rupert 7
 
0.3%
Other values (1462) 1953
94.8%
2025-03-10T21:30:29.518006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1290
 
9.7%
e 1152
 
8.7%
1061
 
8.0%
n 927
 
7.0%
i 894
 
6.7%
r 864
 
6.5%
o 759
 
5.7%
l 626
 
4.7%
t 444
 
3.3%
s 423
 
3.2%
Other values (63) 4840
36.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13280
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1290
 
9.7%
e 1152
 
8.7%
1061
 
8.0%
n 927
 
7.0%
i 894
 
6.7%
r 864
 
6.5%
o 759
 
5.7%
l 626
 
4.7%
t 444
 
3.3%
s 423
 
3.2%
Other values (63) 4840
36.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13280
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1290
 
9.7%
e 1152
 
8.7%
1061
 
8.0%
n 927
 
7.0%
i 894
 
6.7%
r 864
 
6.5%
o 759
 
5.7%
l 626
 
4.7%
t 444
 
3.3%
s 423
 
3.2%
Other values (63) 4840
36.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13280
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1290
 
9.7%
e 1152
 
8.7%
1061
 
8.0%
n 927
 
7.0%
i 894
 
6.7%
r 864
 
6.5%
o 759
 
5.7%
l 626
 
4.7%
t 444
 
3.3%
s 423
 
3.2%
Other values (63) 4840
36.4%

Star4
Text

Distinct939
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
2025-03-10T21:30:29.771910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length27
Median length23
Mean length13.212
Min length4

Characters and Unicode

Total characters13212
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique882 ?
Unique (%)88.2%

Sample

1st rowWilliam Sadler
2nd rowDiane Keaton
3rd rowMichael Caine
4th rowDiane Keaton
5th rowJohn Fiedler
ValueCountFrequency (%)
john 25
 
1.2%
michael 15
 
0.7%
james 12
 
0.6%
richard 9
 
0.4%
lee 9
 
0.4%
bill 8
 
0.4%
mark 8
 
0.4%
kim 7
 
0.3%
charles 7
 
0.3%
martin 7
 
0.3%
Other values (1558) 1962
94.8%
2025-03-10T21:30:30.130870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1284
 
9.7%
e 1128
 
8.5%
1069
 
8.1%
n 903
 
6.8%
r 902
 
6.8%
i 863
 
6.5%
o 710
 
5.4%
l 634
 
4.8%
s 445
 
3.4%
t 419
 
3.2%
Other values (63) 4855
36.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13212
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1284
 
9.7%
e 1128
 
8.5%
1069
 
8.1%
n 903
 
6.8%
r 902
 
6.8%
i 863
 
6.5%
o 710
 
5.4%
l 634
 
4.8%
s 445
 
3.4%
t 419
 
3.2%
Other values (63) 4855
36.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13212
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1284
 
9.7%
e 1128
 
8.5%
1069
 
8.1%
n 903
 
6.8%
r 902
 
6.8%
i 863
 
6.5%
o 710
 
5.4%
l 634
 
4.8%
s 445
 
3.4%
t 419
 
3.2%
Other values (63) 4855
36.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13212
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1284
 
9.7%
e 1128
 
8.5%
1069
 
8.1%
n 903
 
6.8%
r 902
 
6.8%
i 863
 
6.5%
o 710
 
5.4%
l 634
 
4.8%
s 445
 
3.4%
t 419
 
3.2%
Other values (63) 4855
36.7%

No_of_Votes
Real number (ℝ)

Distinct999
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean273692.91
Minimum25088
Maximum2343110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-03-10T21:30:30.214448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum25088
5-th percentile29681
Q155526.25
median138548.5
Q3374161.25
95-th percentile939631.65
Maximum2343110
Range2318022
Interquartile range (IQR)318635

Descriptive statistics

Standard deviation327372.7
Coefficient of variation (CV)1.1961315
Kurtosis6.8950993
Mean273692.91
Median Absolute Deviation (MAD)98663.5
Skewness2.3000106
Sum2.7369291 × 108
Variance1.0717289 × 1011
MonotonicityNot monotonic
2025-03-10T21:30:30.398285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65341 2
 
0.2%
699256 1
 
0.1%
32802 1
 
0.1%
93878 1
 
0.1%
1213505 1
 
0.1%
51853 1
 
0.1%
2343110 1
 
0.1%
1620367 1
 
0.1%
1826188 1
 
0.1%
2067042 1
 
0.1%
Other values (989) 989
98.9%
ValueCountFrequency (%)
25088 1
0.1%
25198 1
0.1%
25229 1
0.1%
25312 1
0.1%
25344 1
0.1%
25938 1
0.1%
26337 1
0.1%
26402 1
0.1%
26429 1
0.1%
26457 1
0.1%
ValueCountFrequency (%)
2343110 1
0.1%
2303232 1
0.1%
2067042 1
0.1%
1854740 1
0.1%
1826188 1
0.1%
1809221 1
0.1%
1676426 1
0.1%
1661481 1
0.1%
1642758 1
0.1%
1620367 1
0.1%

Gross
Text

Missing 

Distinct823
Distinct (%)99.0%
Missing169
Missing (%)16.9%
Memory size52.9 KiB
2025-03-10T21:30:30.606487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.5066185
Min length5

Characters and Unicode

Total characters7900
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique818 ?
Unique (%)98.4%

Sample

1st row28,341,469
2nd row134,966,411
3rd row534,858,444
4th row57,300,000
5th row4,360,000
ValueCountFrequency (%)
4,360,000 5
 
0.6%
5,321,508 2
 
0.2%
9,600,000 2
 
0.2%
5,450,000 2
 
0.2%
25,000,000 2
 
0.2%
96,898,818 1
 
0.1%
30,500,000 1
 
0.1%
216,540,909 1
 
0.1%
292,576,195 1
 
0.1%
28,341,469 1
 
0.1%
Other values (813) 813
97.8%
2025-03-10T21:30:30.886457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 1545
19.6%
0 1117
14.1%
1 775
9.8%
2 677
8.6%
5 639
8.1%
3 597
 
7.6%
4 540
 
6.8%
6 528
 
6.7%
7 510
 
6.5%
8 509
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7900
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 1545
19.6%
0 1117
14.1%
1 775
9.8%
2 677
8.6%
5 639
8.1%
3 597
 
7.6%
4 540
 
6.8%
6 528
 
6.7%
7 510
 
6.5%
8 509
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7900
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 1545
19.6%
0 1117
14.1%
1 775
9.8%
2 677
8.6%
5 639
8.1%
3 597
 
7.6%
4 540
 
6.8%
6 528
 
6.7%
7 510
 
6.5%
8 509
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7900
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 1545
19.6%
0 1117
14.1%
1 775
9.8%
2 677
8.6%
5 639
8.1%
3 597
 
7.6%
4 540
 
6.8%
6 528
 
6.7%
7 510
 
6.5%
8 509
 
6.4%

Interactions

2025-03-10T21:30:23.797376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.310928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.566368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.875911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.408129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.645955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.954562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.487717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-10T21:30:23.722772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-10T21:30:30.946111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
CertificateIMDB_RatingMeta_scoreNo_of_Votes
Certificate1.0000.0000.0880.051
IMDB_Rating0.0001.0000.2850.214
Meta_score0.0880.2851.000-0.072
No_of_Votes0.0510.214-0.0721.000

Missing values

2025-03-10T21:30:24.074928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-10T21:30:24.270551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-03-10T21:30:24.392307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Poster_LinkSeries_TitleReleased_YearCertificateRuntimeGenreIMDB_RatingOverviewMeta_scoreDirectorStar1Star2Star3Star4No_of_VotesGross
0https://m.media-amazon.com/images/M/MV5BMDFkYTc0MGEtZmNhMC00ZDIzLWFmNTEtODM1ZmRlYWMwMWFmXkEyXkFqcGdeQXVyMTMxODk2OTU@._V1_UX67_CR0,0,67,98_AL_.jpgThe Shawshank Redemption1994A142 minDrama9.3Two imprisoned men bond over a number of years, finding solace and eventual redemption through acts of common decency.80.0Frank DarabontTim RobbinsMorgan FreemanBob GuntonWilliam Sadler234311028,341,469
1https://m.media-amazon.com/images/M/MV5BM2MyNjYxNmUtYTAwNi00MTYxLWJmNWYtYzZlODY3ZTk3OTFlXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpgThe Godfather1972A175 minCrime, Drama9.2An organized crime dynasty's aging patriarch transfers control of his clandestine empire to his reluctant son.100.0Francis Ford CoppolaMarlon BrandoAl PacinoJames CaanDiane Keaton1620367134,966,411
2https://m.media-amazon.com/images/M/MV5BMTMxNTMwODM0NF5BMl5BanBnXkFtZTcwODAyMTk2Mw@@._V1_UX67_CR0,0,67,98_AL_.jpgThe Dark Knight2008UA152 minAction, Crime, Drama9.0When the menace known as the Joker wreaks havoc and chaos on the people of Gotham, Batman must accept one of the greatest psychological and physical tests of his ability to fight injustice.84.0Christopher NolanChristian BaleHeath LedgerAaron EckhartMichael Caine2303232534,858,444
3https://m.media-amazon.com/images/M/MV5BMWMwMGQzZTItY2JlNC00OWZiLWIyMDctNDk2ZDQ2YjRjMWQ0XkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR1,0,67,98_AL_.jpgThe Godfather: Part II1974A202 minCrime, Drama9.0The early life and career of Vito Corleone in 1920s New York City is portrayed, while his son, Michael, expands and tightens his grip on the family crime syndicate.90.0Francis Ford CoppolaAl PacinoRobert De NiroRobert DuvallDiane Keaton112995257,300,000
4https://m.media-amazon.com/images/M/MV5BMWU4N2FjNzYtNTVkNC00NzQ0LTg0MjAtYTJlMjFhNGUxZDFmXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpg12 Angry Men1957U96 minCrime, Drama9.0A jury holdout attempts to prevent a miscarriage of justice by forcing his colleagues to reconsider the evidence.96.0Sidney LumetHenry FondaLee J. CobbMartin BalsamJohn Fiedler6898454,360,000
5https://m.media-amazon.com/images/M/MV5BNzA5ZDNlZWMtM2NhNS00NDJjLTk4NDItYTRmY2EwMWZlMTY3XkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UX67_CR0,0,67,98_AL_.jpgThe Lord of the Rings: The Return of the King2003U201 minAction, Adventure, Drama8.9Gandalf and Aragorn lead the World of Men against Sauron's army to draw his gaze from Frodo and Sam as they approach Mount Doom with the One Ring.94.0Peter JacksonElijah WoodViggo MortensenIan McKellenOrlando Bloom1642758377,845,905
6https://m.media-amazon.com/images/M/MV5BNGNhMDIzZTUtNTBlZi00MTRlLWFjM2ItYzViMjE3YzI5MjljXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UY98_CR0,0,67,98_AL_.jpgPulp Fiction1994A154 minCrime, Drama8.9The lives of two mob hitmen, a boxer, a gangster and his wife, and a pair of diner bandits intertwine in four tales of violence and redemption.94.0Quentin TarantinoJohn TravoltaUma ThurmanSamuel L. JacksonBruce Willis1826188107,928,762
7https://m.media-amazon.com/images/M/MV5BNDE4OTMxMTctNmRhYy00NWE2LTg3YzItYTk3M2UwOTU5Njg4XkEyXkFqcGdeQXVyNjU0OTQ0OTY@._V1_UX67_CR0,0,67,98_AL_.jpgSchindler's List1993A195 minBiography, Drama, History8.9In German-occupied Poland during World War II, industrialist Oskar Schindler gradually becomes concerned for his Jewish workforce after witnessing their persecution by the Nazis.94.0Steven SpielbergLiam NeesonRalph FiennesBen KingsleyCaroline Goodall121350596,898,818
8https://m.media-amazon.com/images/M/MV5BMjAxMzY3NjcxNF5BMl5BanBnXkFtZTcwNTI5OTM0Mw@@._V1_UX67_CR0,0,67,98_AL_.jpgInception2010UA148 minAction, Adventure, Sci-Fi8.8A thief who steals corporate secrets through the use of dream-sharing technology is given the inverse task of planting an idea into the mind of a C.E.O.74.0Christopher NolanLeonardo DiCaprioJoseph Gordon-LevittElliot PageKen Watanabe2067042292,576,195
9https://m.media-amazon.com/images/M/MV5BMmEzNTkxYjQtZTc0MC00YTVjLTg5ZTEtZWMwOWVlYzY0NWIwXkEyXkFqcGdeQXVyNzkwMjQ5NzM@._V1_UX67_CR0,0,67,98_AL_.jpgFight Club1999A139 minDrama8.8An insomniac office worker and a devil-may-care soapmaker form an underground fight club that evolves into something much, much more.66.0David FincherBrad PittEdward NortonMeat LoafZach Grenier185474037,030,102
Poster_LinkSeries_TitleReleased_YearCertificateRuntimeGenreIMDB_RatingOverviewMeta_scoreDirectorStar1Star2Star3Star4No_of_VotesGross
990https://m.media-amazon.com/images/M/MV5BYjRmY2VjN2ItMzBmYy00YTRjLWFiMTgtNGZhNWJjMjk3YjZjXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpgGiù la testa1971PG157 minDrama, War, Western7.6A low-life bandit and an I.R.A. explosives expert rebel against the government and become heroes of the Mexican Revolution.77.0Sergio LeoneRod SteigerJames CoburnRomolo ValliMaria Monti30144696,690
991https://m.media-amazon.com/images/M/MV5BMzAyNDUwYzUtN2NlMC00ODliLWExMjgtMGMzNmYzZmUwYTg1XkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpgKelly's Heroes1970GP144 minAdventure, Comedy, War7.6A group of U.S. soldiers sneaks across enemy lines to get their hands on a secret stash of Nazi treasure.50.0Brian G. HuttonClint EastwoodTelly SavalasDon RicklesCarroll O'Connor453381,378,435
992https://m.media-amazon.com/images/M/MV5BMjAwMTExODExNl5BMl5BanBnXkFtZTgwMjM2MDgyMTE@._V1_UX67_CR0,0,67,98_AL_.jpgThe Jungle Book1967U78 minAnimation, Adventure, Family7.6Bagheera the Panther and Baloo the Bear have a difficult time trying to convince a boy to leave the jungle for human civilization.65.0Wolfgang ReithermanPhil HarrisSebastian CabotLouis PrimaBruce Reitherman166409141,843,612
993https://m.media-amazon.com/images/M/MV5BYTE4YWU0NjAtMjNiYi00MTNiLTgwYzctZjk0YjY5NGVhNWQwXkEyXkFqcGdeQXVyMTY5Nzc4MDY@._V1_UY98_CR0,0,67,98_AL_.jpgBlowup1966A111 minDrama, Mystery, Thriller7.6A fashion photographer unknowingly captures a death on film after following two lovers in a park.82.0Michelangelo AntonioniDavid HemmingsVanessa RedgraveSarah MilesJohn Castle56513NaN
994https://m.media-amazon.com/images/M/MV5BZjQyMGUwNzAtNTc2MC00Y2FjLThlM2ItZGRjNzM0OWVmZGYyXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpgA Hard Day's Night1964U87 minComedy, Music, Musical7.6Over two "typical" days in the life of The Beatles, the boys struggle to keep themselves and Sir Paul McCartney's mischievous grandfather in check while preparing for a live television performance.96.0Richard LesterJohn LennonPaul McCartneyGeorge HarrisonRingo Starr4035113,780,024
995https://m.media-amazon.com/images/M/MV5BNGEwMTRmZTQtMDY4Ni00MTliLTk5ZmMtOWMxYWMyMTllMDg0L2ltYWdlL2ltYWdlXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpgBreakfast at Tiffany's1961A115 minComedy, Drama, Romance7.6A young New York socialite becomes interested in a young man who has moved into her apartment building, but her past threatens to get in the way.76.0Blake EdwardsAudrey HepburnGeorge PeppardPatricia NealBuddy Ebsen166544NaN
996https://m.media-amazon.com/images/M/MV5BODk3YjdjZTItOGVhYi00Mjc2LTgzMDAtMThmYTVkNTBlMWVkXkEyXkFqcGdeQXVyNDY2MTk1ODk@._V1_UX67_CR0,0,67,98_AL_.jpgGiant1956G201 minDrama, Western7.6Sprawling epic covering the life of a Texas cattle rancher and his family and associates.84.0George StevensElizabeth TaylorRock HudsonJames DeanCarroll Baker34075NaN
997https://m.media-amazon.com/images/M/MV5BM2U3YzkxNGMtYWE0YS00ODk0LTk1ZGEtNjk3ZTE0MTk4MzJjXkEyXkFqcGdeQXVyNDk0MDg4NDk@._V1_UX67_CR0,0,67,98_AL_.jpgFrom Here to Eternity1953Passed118 minDrama, Romance, War7.6In Hawaii in 1941, a private is cruelly punished for not boxing on his unit's team, while his captain's wife and second-in-command are falling in love.85.0Fred ZinnemannBurt LancasterMontgomery CliftDeborah KerrDonna Reed4337430,500,000
998https://m.media-amazon.com/images/M/MV5BZTBmMjUyMjItYTM4ZS00MjAwLWEyOGYtYjMyZTUxN2I3OTMxXkEyXkFqcGdeQXVyNjc1NTYyMjg@._V1_UX67_CR0,0,67,98_AL_.jpgLifeboat1944NaN97 minDrama, War7.6Several survivors of a torpedoed merchant ship in World War II find themselves in the same lifeboat with one of the crew members of the U-boat that sank their ship.78.0Alfred HitchcockTallulah BankheadJohn HodiakWalter SlezakWilliam Bendix26471NaN
999https://m.media-amazon.com/images/M/MV5BMTY5ODAzMTcwOF5BMl5BanBnXkFtZTcwMzYxNDYyNA@@._V1_UX67_CR0,0,67,98_AL_.jpgThe 39 Steps1935NaN86 minCrime, Mystery, Thriller7.6A man in London tries to help a counter-espionage Agent. But when the Agent is killed, and the man stands accused, he must go on the run to save himself and stop a spy ring which is trying to steal top secret information.93.0Alfred HitchcockRobert DonatMadeleine CarrollLucie MannheimGodfrey Tearle51853NaN